edu.ucar.opensky::articles:42146 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T18:07:15.121982 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.net/ark:/85065/d7nz8cxc https://doi.org/10.3334/ORNLDAAC/1808 https Related Dataset #1 ABoVE: Annual Aboveground Biomass for Boreal Forests of ABoVE Core Domain, 1984-2014 https://doi.org/10.5065/D6RX99HX https Related Service #1 Cheyenne: SGI ICE XA Cluster https://doi.org/10.5281/zenodo.10480768 https Related Software #1 XueliHuo/CTSM: CLM_ABoVE_DA Integrating state data assimilation and innovative model parameterization reduces simulated carbon uptake in the Arctic and boreal region 2024-09-01T00:00:00Z publication https://n2t.net/ark:/85065/d7nz8cxc https://doi.org/10.1029/2024JG008004 Huo, X. author Fox, A. M. author Dashti, H. author Smith, W. K. author Raczka, Brett author Anderson, Jeffrey L. author Rogers, A. author Moore, D. J. P. author UCAR/NCAR - Library publisher Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic&#8208;boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8&#8208;day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. To further reduce the remaining bias in GPP after LAI bias correction, we re&#8208;parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication <style type="text/css"></style><span style="font-family:Arial;font-size:10pt;font-style:normal;" data-sheets-root="1">Copyright 2024 American Geophysical Union.</span> None eng geoscientificInformation